{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-06-11 17:55:43,738 - modelscope - INFO - PyTorch version 2.1.2 Found.\n",
      "2024-06-11 17:55:43,741 - modelscope - INFO - TensorFlow version 2.12.0 Found.\n",
      "2024-06-11 17:55:43,742 - modelscope - INFO - Loading ast index from /home/liyaze/.cache/modelscope/ast_indexer\n",
      "2024-06-11 17:55:43,874 - modelscope - INFO - Loading done! Current index file version is 1.14.0, with md5 45f0cd7d198297b65e8d236e06ce416c and a total number of 976 components indexed\n",
      "/home/liyaze/anaconda3/envs/longchain/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    }
   ],
   "source": [
    "from modelscope.pipelines import pipeline\n",
    "from modelscope.utils.constant import Tasks\n",
    "import cv2\n",
    "import os\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-06-11 17:55:46,024 - modelscope - WARNING - Model revision not specified, use revision: v0.1\n",
      "2024-06-11 17:55:46,229 - modelscope - INFO - initiate model from /home/liyaze/.cache/modelscope/hub/damo/cv_dla34_table-structure-recognition_cycle-centernet\n",
      "2024-06-11 17:55:46,230 - modelscope - INFO - initiate model from location /home/liyaze/.cache/modelscope/hub/damo/cv_dla34_table-structure-recognition_cycle-centernet.\n",
      "2024-06-11 17:55:46,233 - modelscope - WARNING - No preprocessor field found in cfg.\n",
      "2024-06-11 17:55:46,234 - modelscope - WARNING - No val key and type key found in preprocessor domain of configuration.json file.\n",
      "2024-06-11 17:55:46,235 - modelscope - WARNING - Cannot find available config to build preprocessor at mode inference, current config: {'model_dir': '/home/liyaze/.cache/modelscope/hub/damo/cv_dla34_table-structure-recognition_cycle-centernet'}. trying to build by task and model information.\n",
      "2024-06-11 17:55:46,235 - modelscope - WARNING - Find task: table-recognition, model type: None. Insufficient information to build preprocessor, skip building preprocessor\n",
      "2024-06-11 17:55:47,497 - modelscope - INFO - loading model from /home/liyaze/.cache/modelscope/hub/damo/cv_dla34_table-structure-recognition_cycle-centernet/pytorch_model.pt\n"
     ]
    }
   ],
   "source": [
    "table_recognition = pipeline(Tasks.table_recognition, model='damo/cv_dla34_table-structure-recognition_cycle-centernet')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "im = '/home/FAST_DATA_MIRROR/Langchain-Chatchat-master/pdf_tools/output/img/page_13.png'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "result = table_recognition(im)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['polygons'])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f61147d9e10>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# result:\n",
    "# {'polygons': array([[ 778.38794 ,  500.9561  ,  778.4647  ,  597.6962  ,  994.11707 ,\n",
    "#          597.75165 ,  993.9839  ,  500.7736  ],\n",
    "#        [ 778.3362  ,  389.191   ,  778.38794 ,  500.9561  ,  993.9839  ,\n",
    "#          500.7736  ,  994.047   ,  389.2363  ],\n",
    "# 画框\n",
    "im2 = cv2.imread(im)\n",
    "for pts in result['polygons']:\n",
    "    # 画出polygon\n",
    "    pts = pts.reshape((-1, 1, 2))\n",
    "    cv2.polylines(im2, np.int32(pts), True, (255, 0, 0), 3)\n",
    "    \n",
    "plt.imshow(im2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-06-11 18:13:14,084 - modelscope - WARNING - Model revision not specified, use revision: v2.4.0\n",
      "Downloading: 100%|██████████| 1.51k/1.51k [00:00<00:00, 6.00MB/s]\n",
      "Downloading: 100%|██████████| 100k/100k [00:00<00:00, 1.18MB/s]\n",
      "Downloading: 100%|██████████| 73.3M/73.3M [00:46<00:00, 1.66MB/s]\n",
      "Downloading: 100%|██████████| 73.3M/73.3M [00:36<00:00, 2.10MB/s]\n",
      "Downloading: 100%|██████████| 5.14k/5.14k [00:00<00:00, 7.45MB/s]\n",
      "Downloading: 100%|██████████| 8.85k/8.85k [00:00<00:00, 15.3MB/s]\n",
      "Downloading: 100%|██████████| 52.0k/52.0k [00:00<00:00, 2.31MB/s]\n",
      "Downloading: 100%|██████████| 29.6k/29.6k [00:00<00:00, 2.94MB/s]\n",
      "2024-06-11 18:14:39,836 - modelscope - INFO - initiate model from /home/liyaze/.cache/modelscope/hub/damo/cv_convnextTiny_ocr-recognition-document_damo\n",
      "2024-06-11 18:14:39,837 - modelscope - INFO - initiate model from location /home/liyaze/.cache/modelscope/hub/damo/cv_convnextTiny_ocr-recognition-document_damo.\n",
      "2024-06-11 18:14:39,838 - modelscope - INFO - initialize model from /home/liyaze/.cache/modelscope/hub/damo/cv_convnextTiny_ocr-recognition-document_damo\n",
      "2024-06-11 18:14:40,098 - modelscope - INFO - loading model from dir /home/liyaze/.cache/modelscope/hub/damo/cv_convnextTiny_ocr-recognition-document_damo\n",
      "2024-06-11 18:14:40,142 - modelscope - INFO - loading model done\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'text': ['丙方(签字并按指印)']}\n"
     ]
    }
   ],
   "source": [
    "from modelscope.pipelines import pipeline\n",
    "from modelscope.utils.constant import Tasks\n",
    "import cv2\n",
    "\n",
    "ocr_recognition = pipeline(Tasks.ocr_recognition, model='damo/cv_convnextTiny_ocr-recognition-document_damo')\n",
    "\n",
    "### 使用url\n",
    "img_url = 'http://duguang-labelling.oss-cn-shanghai.aliyuncs.com/mass_img_tmp_20220922/ocr_recognition_document.png'\n",
    "result = ocr_recognition(img_url)\n",
    "print(result)\n",
    "\n",
    "### 使用图像文件\n",
    "### 请准备好名为'ocr_recognition.jpg'的图像文件\n",
    "# img_path = 'ocr_recognition.jpg'\n",
    "# img = cv2.imread(img_path)\n",
    "# result = ocr_recognition(img)\n",
    "# print(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-06-11 18:14:43,330 - modelscope - INFO - Use user-specified model revision: v1.0.0\n",
      "Downloading: 100%|██████████| 447/447 [00:00<00:00, 1.61MB/s]\n",
      "Downloading: 100%|██████████| 5.79M/5.79M [00:00<00:00, 6.35MB/s]\n",
      "Downloading: 100%|██████████| 4.77k/4.77k [00:00<00:00, 7.70MB/s]\n",
      "2024-06-11 18:14:45.639775: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
      "2024-06-11 18:14:45.686856: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
      "To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
      "2024-06-11 18:14:47,464 - modelscope - INFO - initiate model from /home/liyaze/.cache/modelscope/hub/damo/cv_proxylessnas_ocr-detection-db-line-level_damo\n",
      "2024-06-11 18:14:47,465 - modelscope - INFO - initiate model from location /home/liyaze/.cache/modelscope/hub/damo/cv_proxylessnas_ocr-detection-db-line-level_damo.\n",
      "2024-06-11 18:14:47,466 - modelscope - INFO - initialize model from /home/liyaze/.cache/modelscope/hub/damo/cv_proxylessnas_ocr-detection-db-line-level_damo\n",
      "2024-06-11 18:14:47,545 - modelscope - INFO - loading model from dir /home/liyaze/.cache/modelscope/hub/damo/cv_proxylessnas_ocr-detection-db-line-level_damo\n",
      "2024-06-11 18:14:47,564 - modelscope - INFO - loading model done\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'polygons': array([[424, 736, 779, 736, 779, 780, 424, 780],\n",
      "       [ 25, 735, 443, 735, 443, 783,  25, 783],\n",
      "       [196, 375, 597, 375, 597, 420, 196, 420],\n",
      "       [692, 205, 772, 205, 772, 246, 692, 246],\n",
      "       [541, 204, 621, 204, 621, 245, 541, 245],\n",
      "       [542, 160, 623, 160, 623, 201, 542, 201],\n",
      "       [691, 158, 773, 158, 773, 199, 691, 199],\n",
      "       [223,  20, 776,  20, 776,  60, 223,  60],\n",
      "       [  0, 117, 109,   0, 148,  34,  28, 154]])}\n"
     ]
    },
    {
     "ename": "",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31mThe Kernel crashed while executing code in the current cell or a previous cell. \n",
      "\u001b[1;31mPlease review the code in the cell(s) to identify a possible cause of the failure. \n",
      "\u001b[1;31mClick <a href='https://aka.ms/vscodeJupyterKernelCrash'>here</a> for more info. \n",
      "\u001b[1;31mView Jupyter <a href='command:jupyter.viewOutput'>log</a> for further details."
     ]
    }
   ],
   "source": [
    "from modelscope.pipelines import pipeline\n",
    "from modelscope.utils.constant import Tasks\n",
    "ocr_detection = pipeline(Tasks.ocr_detection, model='damo/cv_proxylessnas_ocr-detection-db-line-level_damo', model_revision='v1.0.0')\n",
    "result = ocr_detection('https://modelscope.oss-cn-beijing.aliyuncs.com/test/images/ocr_detection.jpg')\n",
    "print(result)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "longchain",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.1.-1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
